An indicative end-milling condition decision support system using data-mining for difficult-to-cut materials based on comparison with irregular pitch and lead end-mill and general purpose end-mill

Hiroyuki Kodama, Toshiki Hirogaki, Eiichi Aoyama, Keiji Ogawa

研究成果

1 被引用数 (Scopus)

抄録

Data-mining methods using hierarchical and non-hierarchical clustering are proposed that will help engineers determine appropriate end-milling conditions. We have constructed a system that uses clustering techniques and tool catalog data to support the determination of end-milling conditions for different types of difficult-to-cut materials such as austenitic stainless steel, Ni-base superalloy, and titanium alloy. Variable cluster analysis and the K-means method were used together to identify tool shape parameters that have a linear relationship with the end-milling conditions listed in the catalogs. The response surface method and significant tool shape parameters obtained by clustering were used to derive end-milling condition decision equations, which were used to determine the indicative end-milling conditions for each material. Comparison with the conditions recommended by toolmakers demonstrated that our proposed system can be used to determine the cutting speeds for various difficult-to-cut materials.

本文言語English
ホスト出版物のタイトルAdvances in Abrasive Technology XVI
ページ177-182
ページ数6
DOI
出版ステータスPublished - 2013
外部発表はい
イベント16th International Symposium on Advances in Abrasive Technology, ISAAT 2013 and 17th Chinese Conference of Abrasive Technology, CCAT 2013 - Hangzhou
継続期間: 9月 23 20139月 26 2013

出版物シリーズ

名前Advanced Materials Research
797
ISSN(印刷版)1022-6680

Other

Other16th International Symposium on Advances in Abrasive Technology, ISAAT 2013 and 17th Chinese Conference of Abrasive Technology, CCAT 2013
国/地域China
CityHangzhou
Period9/23/139/26/13

ASJC Scopus subject areas

  • 工学一般

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